1. Technical Field
The technology disclosed herein relates to an increase in the resolution of an imaging apparatus such as a digital still camera.
2. Background Information
In recent years, attention has been focused on so-called super-resolution technology, which is technology for improving the resolution of images handled by digital still cameras and digital televisions. A typical example of super-resolution technology is technology for generating one high-resolution image with use of a plurality of continuously captured images or consecutive frames in a moving image (e.g., see JP 2006-39628A and JP 2008-294950A, which are hereinafter referred to as “Patent Document 1” and “Patent Document 2” respectively). The temporally consecutive images are analyzed, and position shift of objects that has occurred between images is calculated. A high-resolution image is then estimated and generated by superimposing the frame images based on the calculated position shift.
However, with many digital still cameras, the pixels of the imaging element are generally provided with different-colored color filters arranged in a predetermined pattern in order to obtain color images. FIG. 12 shows an example of the pattern of a Bayer array imaging element, which is often used in digital still cameras, and as shown in FIG. 12, there is a row in which a blue (B) filter and a green (G) filter are alternately arranged and a row in which a green (G) filter and a red (R) filter are alternately arranged, and these two rows are provided alternately. In this case, the pixels that receive green light, which has the greatest influence on resolution, are arranged in a hound's tooth configuration, and interpolation processing is performed for the pixels therebetween that cannot receive green light. For this reason, the image obtained from light that has passed through the green (G) filter is obtained at a lower sampling frequency than the sampling frequency of the imaging element. The sampling frequencies of the pixels that receive blue light and the pixels that receive red light are even lower. Accordingly, the resolution characteristics of the luminance component calculated from the images obtained by the three colors of filters are more degraded than the case where light is received by all of the pixels, as with a monochrome camera. In other words, there is the problem that the resolution characteristics degrade as a trade-off for obtaining color information.
Accordingly, in the images that are used, the resolution characteristics in the vicinity of the Nyquist frequency are more degraded than the characteristics of the lens optical system, and therefore even if pixel data for a high-resolution image is obtained by performing position correction, superimposition, and interpolation processing as in the disclosure of Patent Document 1, it is not possible to restore the resolution characteristics in the vicinity of the Nyquist frequency of the original image.
Also, with a technique of minimizing the evaluation function through a repetitive computation such as in Patent Document 2, degraded resolution can be expected to be restored to a certain extent, but such a technique is not practical due to the computation load being very high.